There is now an increased importance in analyzing the electricity sector. The increased efforts to reach carbon neutrality have made renewable energy sourcesRenewable Energy Sources (RES) and distributed generationDistributed generation a staple of modern electricity systems. While inevitable, the transition to renewable energy brings along several issues, such as the intermittency and unpredictability of generation. The consideration for this concern is imperative when studying factors related to the network. Other factors of importance to consider when modeling modern medium-voltage networks are the remuneration of distributed generationDistributed generation, carbon emissionsCarbon emissions, risk-aversion through metrics such as conditional value-at-riskConditional value-at-risk, multiple investment periods, and more standardized implementations such as energy storage systemsEnergy Storage System (ESS) and electric vehiclesElectric vehicles. The proposed model addresses all these issues with a special focus on uncertaintyUncertainty management, looking at the issue through a daily, and seasonal lens. Additionally, there is also an assessment of network reliability and an economic analysisEconomic analysis. Unlike prior research, this model uniquely integrates a comprehensive set of factors, including distributed remuneration, carbon emissionsCarbon emissions, multi-period-investments, and CVaR-based risk-aversion, while addressing daily and seasonal uncertaintiesSeasonal uncertainty. The model is tested on a 180-bus medium voltageMedium voltage distribution networkDistribution network in Portugal and is appealing economically. For no risk aversionRisk aversion it obtained a payback on investment of 8.98 years.